SplitFusion: Simultaneous Tracking and Mapping for Non-Rigid Scenes
Yang Li,Tianwei Zhang,Yoshihiko Nakamura,Tatsuya Harada,Yang Li,Tianwei Zhang,Yoshihiko Nakamura,Tatsuya Harada
We present SplitFusion, a novel dense RGB-D SLAM framework that simultaneously performs tracking and dense reconstruction for both rigid and non-rigid components of the scene. SplitFusion first adopts deep learning based semantic instant segmentation technique to split the scene into rigid or non-rigid surfaces. The split surfaces are independently tracked via rigid or non-rigid ICP and reconstruc...
